Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Location models for airline hubs behaving as M/D/c queues
Computers and Operations Research
An Exact Solution Approach Based on Shortest-Paths for P-Hub Median Problems
INFORMS Journal on Computing
Approximation Algorithms for Data Distribution with Load Balancing of Web Servers
CLUSTER '01 Proceedings of the 3rd IEEE International Conference on Cluster Computing
Genetic Algorithm with Multistart Search for the p-Hub Median Problem
EUROMICRO '98 Proceedings of the 24th Conference on EUROMICRO - Volume 2
Capacitated single allocation hub location problem-A bi-criteria approach
Computers and Operations Research
An Evolutionary Metaheuristic for Approximating Preference-Nondominated Solutions
INFORMS Journal on Computing
A favorable weight-based evolutionary algorithm for multiple criteria problems
IEEE Transactions on Evolutionary Computation
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
The balance between proximity and diversity in multiobjective evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Twenty-Five Years of Hub Location Research
Transportation Science
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In this paper, we present two bicriteria uncapacitated, multiple allocation p-hub location problems. In the first problem, our first objective is to minimize the total transportation costs of the uncapacitated multiple allocation p-hub median problem with a positive interhub transfer cost. Our second objective is to minimize the total traveling costs between hub points and origin--destination points. In this case, the interhub transfer cost is negligible, and the problem turns into a well-known facility location problem, i.e., the p-median problem. In the second problem, we address the delays occurring with the congestion during service at the hubs. We consider the trade-off between our first objective and a new objective function, which is to minimize the maximum delay at each hub. We propose bicriteria evolutionary algorithms to approximate the efficient frontiers of these problems. We test the performance of our algorithm on Turkish Postal System, Australian Post, and U.S. Civil Aeronautics Board data sets.